Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: receiving via a computer network a first user input associated with a game; determining based on the first user input a current state of the game; while the current state of the game is being determined, predicting a next state of the game based on the first user input and one or more predicted user inputs; determining that a second user input different from the one or more predicted user inputs is received via the computer network, wherein the second user input is received during said predicting the next state of the game; generating a game state based on the second user input; generating one or more frames based on the game state, wherein said generating the game state based on the second user input and generating the one or more frames based on the game state are provided a higher priority than said predicting the next state of the game; and sending via the computer network the one or more frames generated based on the game state.
2. The method of claim 1 , further comprising generating, by a graphics engine, one or more predicted frames based on the next state, wherein said predicting the next state of the game and said generating the one or more predicted frames are performed before the one or more predicted user inputs are received to reduce a latency in execution of the game.
3. A method comprising: receiving via a computer network a first user input associated with a game; determining based on the first user input a current state of the game; while the current state of the game is being determined, predicting a next state of the game based on the first user input and one or more predicted user inputs; generating, by a graphics engine, one or more predicted frames based on the next state; determining that a second user input different from the one or more predicted user inputs is received via the computer network, wherein the second user input is received during said generating the one or more predicted frames; generating a game state based on the second user input; generating one or more frames based on the game state, wherein said generating the game state based on the second user input and generating the one or more frames based on the game state are provided a higher priority than said generating the one or more predicted frames; and sending via the computer network the one or more frames generated based on the game state.
4. The method of claim 1 , wherein said predicting the next state of the game is based on an output of the current state of the game.
5. A method comprising: receiving via a computer network a first user input associated with a game; determining based on the first user input a current state of the game; while the current state of the game is being determined, predicting a next state of the game based on the first user input and one or more predicted user inputs; generating, by a graphics engine, one or more predicted frames based on the next state; determining that a second user input different from the one or more predicted user inputs is received via the computer network; generating one or more elements of a game state of the game based on the second user input, wherein the one or more elements are not within the next state; generating one or more frames based on the one or more elements of the game state; and sending the one or more frames generated based on the one or more elements of the game state for allowing a display of one or more composite images, wherein the one or more composite images have the one or more elements of the game state superimposed on the one or more predicted frames.
6. The method of claim 1 , further comprising: determining whether a complex physics state is to be determined in said predicting the next state of the game; providing a task of said determining the complex physics state to a node; and retaining a task of determining a simple physics state in said predicting the next state of the game.
7. The method of claim 6 , wherein the complex physics state includes contact points of collision of two virtual objects in the game and the simple physics state includes an occurrence of the collision.
8. The method of claim 1 , wherein the one or more predicted frames have a simple graphics state, the method further comprising: generating, by a graphics engine, one or more predicted frames based on the next state; determining whether a complex graphics state is to be determined in said predicting the next state of the game; providing a task of said determining the complex graphics state to a node; receiving one or more images frames for the complex graphics state from the node; and combining the one or more frames for the complex graphics state with the one or more predicted frames.
9. The method of claim 1 , further comprising: determining whether a complex artificial intelligence state is to be determined in said predicting the next state of the game; providing a task of said determining the complex artificial intelligence state to a node; and retaining a task of determining a simple artificial intelligence state in said predicting the next state of the game.
10. The method of claim 1 , further comprising generating, by a graphics engine, one or more predicted frames based on the next state, wherein the one or more predicted frames include image frames or audio frames or both image frames and audio frames.
11. A system comprising: a first node configured to: receive via a computer network a first user input associated with a game; determine based on the first user input a current state of the game; a second node coupled to the first node, wherein the second node is configured to: receive the first user input associated with the game from the first node; predict a next state of the game based on the first user input and one or more predicted user inputs while the current state of the game is being determined; determine that a second user input different from the one or more predicted user inputs is received via the computer network, wherein one of the first node and the second node is configured to: generate a game state based on the second user input; generate one or more frames based on the game state, wherein the game state and the one or more frames are generated with a higher priority than the prediction of the next state by the second node; and send via the computer network the one or more frames generated based on the game state.
12. The system of claim 11 , wherein the second node is configured to predict the next state of the game and generate one or more predicted frames based on the next state before the one or more predicted user inputs are received to reduce a latency in execution of the game.
This invention relates to a system for reducing latency in game execution by predicting future game states and generating predicted frames in advance. The system operates in a distributed computing environment where a first node receives user inputs and a second node processes game logic and renders frames. The second node predicts the next state of the game and generates one or more predicted frames based on this next state before receiving the actual user inputs. This precomputation allows the system to quickly display the predicted frames when the user inputs are received, minimizing delays in game execution. The system may also compare the predicted frames with actual frames generated after receiving the user inputs to determine if the predictions were accurate. If discrepancies are found, the system adjusts the prediction model to improve future accuracy. The invention is particularly useful in online multiplayer games or cloud-based gaming systems where network latency can significantly impact gameplay responsiveness. By anticipating user actions and pre-rendering frames, the system ensures smoother and more responsive gameplay.
13. A system comprising: a first node configured to: receive via a computer network a first user input associated with a game; determine based on the first user input a current state of the game; a second node coupled to the first node, wherein the second node is configured to: receive the first user input associated with the game from the first node; predict a next state of the game based on the first user input and one or more predicted user inputs while the current state of the game is being determined; generate, using a graphical engine, one or more predicted frames based on the next state; determine that a second user input different from the one or more predicted user inputs is received via the computer network, wherein one of the first node and the second node is configured to: generate a game state based on the second user input; generate one or more frames based on the game state, wherein the game state and the one or more frames are generated with a higher priority than the generation of the one or more predicted frames by the second node; and send via the computer network the one or more frames generated based on the game state.
This system aims to reduce latency in games by anticipating future states. It includes a first computing node that receives initial user input and determines the current state of a game. A second node, connected to the first, also receives this input. While the current game state is being determined, this second node predicts a "next state" based on the initial user input and its own predictions of future user inputs. It then uses a graphics engine to generate speculative "predicted frames" based on this predicted next state. If a different, actual second user input is received (one not matching the predicted inputs), either the first or second node immediately generates a definitive game state based on this real input and creates corresponding frames. Critically, generating this actual game state and its frames is given a higher processing priority than the ongoing generation of the speculative predicted frames. Finally, these accurately generated frames, reflecting the actual user input, are sent over the network.
14. The system of claim 11 , wherein the second node is configured to predict the next state of the game based on an output of the current state of the game.
This invention relates to a system for predicting game states in a multiplayer game environment. The system addresses the challenge of accurately forecasting future game conditions based on real-time player interactions and game dynamics. The system includes a network of interconnected nodes, where a first node collects and processes game state data, such as player positions, scores, and environmental factors. A second node, connected to the first node, uses this data to predict the next state of the game. The prediction is generated by analyzing the current state of the game and applying machine learning or statistical models to estimate probable outcomes. The system may also include a third node that validates the predicted state by comparing it with actual game progression, ensuring accuracy and refining the prediction algorithms over time. The system is designed to enhance gameplay by providing real-time insights, optimizing strategic decisions, and improving player experience through adaptive gameplay adjustments. The invention is particularly useful in competitive multiplayer games where anticipating opponent moves and environmental changes is critical for success.
15. A system comprising: a first node configured to: receive via a computer network a first user input associated with a game; determine from the first user input a current state of the game; a second node coupled to the first node, wherein the second node is configured to: receive the first user input associated with the game from the first node; predict a next state of the game based on the first user input and one or more predicted user inputs while the current state of the game is being determined; generate, using a graphical engine, one or more predicted frames based on the next state; wherein one of the first node and the second node is configured to: determine that a second user input different from the one or more predicted user inputs is received via the computer network; generate one or more elements of a game state of the game based on the second user input, wherein the one or more elements of the game state are not within the next state; generate one or more frames based on the one or more elements of the game state; and send the one or more frames generated based on the one or more elements of the game state for allowing a display of one or more composite images, wherein the one or more composite images have the one or more elements of the game state superimposed on the one or more predicted frames.
16. The system of claim 11 , further comprising: a third node coupled to the second node, wherein the second node is configured to: determine whether a complex physics state is to be determined to predict the next state of the game; provide a task of the determination of the complex physics state to the third node; and retain a task of determining a simple physics state for the prediction of the next state of the game.
This invention relates to distributed computing systems for game simulations, specifically addressing the challenge of efficiently handling complex physics calculations in real-time gaming environments. The system includes a network of nodes where computational tasks are dynamically allocated based on complexity. A primary node manages game state predictions, while secondary nodes handle computationally intensive physics calculations. The system further includes a third node coupled to a secondary node, enabling delegation of complex physics state determinations to this third node. The secondary node evaluates whether a complex physics state must be calculated to predict the next game state. If so, it offloads this task to the third node while retaining simpler physics calculations for itself. This distributed approach optimizes performance by balancing workload across nodes, ensuring real-time responsiveness without overburdening any single node. The system dynamically adjusts task allocation based on computational demands, improving efficiency in physics-heavy simulations. This architecture is particularly useful in multiplayer or high-fidelity game environments where accurate physics modeling is critical but computationally expensive.
17. The system of claim 16 , wherein the complex physics state includes contact points of collision of two virtual objects in the game and the simple physics state includes an occurrence of the collision.
18. The system of claim 11 , wherein the second node is configured to generate, using a graphical engine, one or more predicted frames based on the next state, wherein the one or more predicted frames have a simple graphics state, the system further comprising: a third node coupled to the second node, wherein the second node is configured to: determine whether a complex graphics state is to be determined to predict the next state of the game; provide a task of the determination of the complex graphics state to the third node; receive one or more images frames for the complex graphics state from the third node; and combine the one or more frames for the complex graphics state with the one or more predicted frames.
19. The system of claim 11 , further comprising: a third node coupled to the second node, wherein the second node is configured to: determine whether a complex artificial intelligence state is to be determined to predict the next state of the game; provide a task of the determination of the complex artificial intelligence state to the third node; and retain a task of determining a simple artificial intelligence state for the prediction of the next state of the game.
This invention relates to a distributed artificial intelligence (AI) system for game state prediction, addressing the challenge of efficiently managing computational resources in AI-driven gaming environments. The system includes a network of nodes where a second node is responsible for determining whether a complex AI state is needed to predict the next game state. If a complex AI state is required, the second node delegates the task to a third node, while retaining the simpler AI state determination tasks for itself. This distributed approach optimizes resource allocation by offloading computationally intensive tasks to specialized nodes, improving performance and scalability. The system ensures that only necessary complex AI computations are performed, reducing unnecessary processing overhead. The second node acts as an intermediary, dynamically assigning tasks based on complexity, while the third node handles the more demanding AI state calculations. This architecture enhances efficiency in real-time gaming applications by balancing workload distribution across nodes. The invention is particularly useful in multiplayer or AI-driven games where rapid and accurate state predictions are critical for gameplay.
20. The system of claim 11 , wherein the second node is configured to generate, using a graphical engine, one or more predicted frames based on the next state, wherein the one or more predicted frames include image frames or audio frames or both image frames and audio frames.
This invention relates to a system for generating predicted frames in a distributed computing environment. The system addresses the challenge of efficiently predicting future states in dynamic environments, such as simulations, gaming, or real-time applications, where accurate and timely frame generation is critical. The system includes a first node that determines a next state of an environment based on input data, such as sensor readings or user inputs. This next state represents a future condition of the environment. A second node, connected to the first node, receives the next state and uses a graphical engine to generate predicted frames. These frames can be image frames, audio frames, or a combination of both, depending on the application. The graphical engine processes the next state to produce visual or auditory representations of the predicted environment. The system ensures that the predicted frames are generated in real-time or near-real-time, enabling applications like virtual reality, augmented reality, or autonomous systems to respond dynamically to changing conditions. The use of a distributed architecture allows for parallel processing, improving efficiency and reducing latency. The invention enhances the accuracy and responsiveness of predictive systems in environments where rapid frame generation is essential.
Unknown
February 23, 2021
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